/*
 * Tencent is pleased to support the open source community by making Angel available.
 *
 * Copyright (C) 2017 THL A29 Limited, a Tencent company. All rights reserved.
 *
 *  Licensed under the BSD 3-Clause License (the "License"); you may not use this file except in
 * compliance with the License. You may obtain a copy of the License at
 *
 *  https://opensource.org/licenses/BSD-3-Clause
 *
 *  Unless required by applicable law or agreed to in writing, software distributed under the License
 *  is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
 *  or implied. See the License for the specific language governing permissions and limitations under
 *  the License.
 *
 */

package com.tencent.angel.serving.client

import com.tencent.angel.ml.math.TVector
import com.tencent.angel.serving.{PredictData, PredictResult}

/**
  * the default model coordinator
  *
  */
class DefaultModelCoordinator(name: String, servingClient: ServingClient) extends ModelCoordinator {

  lazy val router = servingClient.getRouter(name)

  val batchSize = 10

  override def predict[V <: TVector](data: PredictData[V]): PredictResult = {
    val results = router.route(data).par.map(predictSplit => router.predict(predictSplit)).toArray
    new PredictResult(results.map(result => result.score).sum)
  }
}
